root/llama.cpp
1
0
Fork 0
mirror of https://github.com/ggerganov/llama.cpp.git synced 2024-12-28 12:24:35 +00:00
Code Issues Actions 3 Packages Projects Releases Wiki Activity

attempt to get test-backend-ops working

Browse Source
This commit is contained in:
Jared Van Bortel 2024-01-10 16:14:03 -05:00
parent 8a99f69895
commit 50579f27e9
3 changed files with 108 additions and 5 deletions
Show Stats Download Patch File Download Diff File Expand all files Collapse all files

6
ggml-backend.c
View File

@ -314,6 +314,12 @@ static void ggml_backend_registry_init(void) {
extern ggml_backend_buffer_type_t ggml_backend_metal_buffer_type(void);
ggml_backend_register("Metal", ggml_backend_reg_metal_init, ggml_backend_metal_buffer_type(), NULL);
#endif
#ifdef GGML_USE_KOMPUTE
extern ggml_backend_t ggml_backend_reg_kompute_init(const char * params, void * user_data);
extern ggml_backend_buffer_type_t ggml_backend_kompute_buffer_type(void);
ggml_backend_register("Kompute", ggml_backend_reg_kompute_init, ggml_backend_kompute_buffer_type(), NULL);
#endif
}
void ggml_backend_register(const char * name, ggml_backend_init_fn init_fn, ggml_backend_buffer_type_t default_buffer_type, void * user_data) {

99
ggml-kompute.cpp
View File

@ -499,7 +499,7 @@ ggml_vk_memory * ggml_vk_find_tensor(struct ggml_kompute_context * ctx, struct g
const intptr_t ioffs = reinterpret_cast<intptr_t>(t->data) - reinterpret_cast<intptr_t>(buf_ctx->data);
GGML_ASSERT(ioffs >= 0 && ioffs + ggml_nbytes(t) <= (int64_t)t->buffer->size);
GGML_ASSERT(ioffs >= 0 && ioffs + (int64_t)ggml_nbytes(t) <= (int64_t)t->buffer->size);
offset = (uint64_t)ioffs;
return buf_ctx;
@ -1344,6 +1344,82 @@ static void ggml_vk_cpy_f16_f32(Args&&... args) {
ggml_vk_cpy<2, 4>(spirv, std::forward<Args>(args)...);
}
static bool ggml_kompute_supports_op(const struct ggml_tensor * op) {
switch (op->type) {
case GGML_TYPE_F16:
case GGML_TYPE_F32:
case GGML_TYPE_Q4_0:
case GGML_TYPE_Q4_1:
break;
default:
return false;
}
switch (op->op) {
case GGML_OP_UNARY:
switch (ggml_get_unary_op(op)) {
case GGML_UNARY_OP_RELU:
case GGML_UNARY_OP_GELU:
case GGML_UNARY_OP_SILU:
return true;
default:
;
}
break;
case GGML_OP_NONE:
case GGML_OP_RESHAPE:
case GGML_OP_VIEW:
case GGML_OP_TRANSPOSE:
case GGML_OP_PERMUTE:
case GGML_OP_CONCAT:
case GGML_OP_ADD:
case GGML_OP_ACC:
case GGML_OP_MUL:
case GGML_OP_DIV:
case GGML_OP_SCALE:
case GGML_OP_SQR:
case GGML_OP_SUM_ROWS:
case GGML_OP_SOFT_MAX:
case GGML_OP_RMS_NORM:
case GGML_OP_GROUP_NORM:
case GGML_OP_NORM:
case GGML_OP_ALIBI:
case GGML_OP_ROPE:
case GGML_OP_IM2COL:
case GGML_OP_UPSCALE:
case GGML_OP_PAD:
case GGML_OP_ARGSORT:
case GGML_OP_LEAKY_RELU:
case GGML_OP_MUL_MAT:
case GGML_OP_MUL_MAT_ID:
return true;
case GGML_OP_DUP:
case GGML_OP_CPY:
case GGML_OP_CONT:
switch (op->src[0]->type) {
case GGML_TYPE_F32:
case GGML_TYPE_F16:
break;
default:
return false;
}
switch (op->type) {
case GGML_TYPE_F32:
case GGML_TYPE_F16:
break;
default:
return false;
}
return true;
case GGML_OP_DIAG_MASK_INF:
case GGML_OP_GET_ROWS:
return op->ne[3] == 1;
default:
;
}
return false;
}
void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml_cgraph * gf) {
const int n_seq = 8;
@ -1362,7 +1438,7 @@ void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml_cgraph
auto& seq = *sequences[seq_idx];
const int node_start = (seq_idx + 0) * n_nodes_per_seq;
const int node_end = (seq_idx == n_seq - 1) ? gf->n_nodes : (seq_idx + 1) * n_nodes_per_seq;
const int node_end = std::min((seq_idx == n_seq - 1) ? gf->n_nodes : (seq_idx + 1) * n_nodes_per_seq, gf->n_nodes);
for (int i = node_start; i < node_end; ++i) {
struct ggml_tensor * src0 = gf->nodes[i]->src[0];
@ -1381,6 +1457,11 @@ void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml_cgraph
break;
}
if (!ggml_kompute_supports_op(dst)) {
fprintf(stderr, "%s: error: unsupported op '%s'\n", __func__, ggml_op_desc(dst));
GGML_ASSERT(!"unsupported op");
}
const int32_t ne00 = src0 ? src0->ne[0] : 0;
const int32_t ne01 = src0 ? src0->ne[1] : 0;
const int32_t ne02 = src0 ? src0->ne[2] : 0;
@ -1718,7 +1799,7 @@ static bool ggml_backend_kompute_buffer_type_supports_backend(ggml_backend_buffe
return ggml_backend_is_kompute(backend);
}
ggml_backend_buffer_type_t ggml_backend_kompute_buffer_type(void) {
ggml_backend_buffer_type_t ggml_backend_kompute_buffer_type() {
static struct ggml_backend_buffer_type ggml_backend_buffer_type_kompute = {
/* .iface = */ {
/* .get_name = */ ggml_backend_kompute_buffer_type_get_name,
@ -1761,8 +1842,7 @@ static bool ggml_backend_kompute_graph_compute(ggml_backend_t backend, struct gg
static bool ggml_backend_kompute_supports_op(ggml_backend_t backend, const struct ggml_tensor * op) {
GGML_UNUSED(backend);
GGML_UNUSED(op);
return true; // TODO: implement
return ggml_kompute_supports_op(op);
}
static struct ggml_backend_i kompute_backend_i = {
@ -1800,3 +1880,12 @@ ggml_backend_t ggml_backend_kompute_init() {
bool ggml_backend_is_kompute(ggml_backend_t backend) {
return backend && backend->iface.get_name == ggml_backend_kompute_name;
}
extern "C" ggml_backend_t ggml_backend_reg_kompute_init(const char * params, void * user_data);
ggml_backend_t ggml_backend_reg_kompute_init(const char * params, void * user_data) {
GGML_UNUSED(params);
GGML_UNUSED(user_data);
ggml_vk_init_device(0, "gpu");
return ggml_backend_kompute_init();
}

8
ggml-kompute.h
View File

@ -63,6 +63,10 @@ void ggml_vk_graph_compute(struct ggml_kompute_context * ctx, struct ggml_cgraph
// user-code should use only these functions
//
#ifdef __cplusplus
extern "C" {
#endif
// forward declaration
typedef struct ggml_backend * ggml_backend_t;
@ -71,3 +75,7 @@ GGML_API ggml_backend_t ggml_backend_kompute_init(void);
GGML_API bool ggml_backend_is_kompute(ggml_backend_t backend);
GGML_API ggml_backend_buffer_type_t ggml_backend_kompute_buffer_type(void);
#ifdef __cplusplus
}
#endif